For an appropriate determination of hydrocarbon reserves contained in a reservoir, it is useful to establish grids (or mesh models) of the reservoir, for example on the basis of 3D seismic interpretation of the subsurface.
These models must be determined in order to represent as accurately as possible the actual subsurface containing the reservoir.
In the petroleum industry, a well test can provide better understanding of the properties of hydrocarbons and allow determining the characteristics of the reservoir where the hydrocarbons are trapped. Most often, a well test includes alternating phases of drawdown and buildup of the well concerned; the flow and pressure variations over time are recorded. The document “Well testing interpretation method (Fundamentals of Exploration and Production), Gilles Bourdarot, Institut Français du Pétrole Publications, ISSN 1271-9048” or the document “Well test analysis: the use of advanced interpretation method, Dominique Bourdet, Elsevier, ISBN 0444509682” present a number of methods for interpreting these flow and pressure variations.
One objective of a well test may be to determine the capacity of the reservoir for producing hydrocarbons such as oil or natural gas.
Another purpose of such a test may be descriptive, i.e. to determine the reservoir geometry and characteristics (rock porosity, presence of boundaries, etc.).
The set of information determined using these well tests is called “dynamic modeling constraints” (for example the volume connected to the well, the presence of reservoir boundaries and associated distance(s), flow properties of fluids flowing to the well, rock porosity, permeability, etc.).
To satisfy dynamic modeling constraints, well engineers or geologists usually determine a large number of “candidate” models by means of known methodologies (for example such as those described in patent application FR1257649 for the determination of channels), then eliminate the models that do not satisfy these dynamic constraints (possibly with a given margin of tolerance).
Such methods are not without flaws, however.
Only a small number of models (possibly having a random portion) will statistically satisfy the dynamic constraints.
Thus, fully calculating the models that are eventually set aside consumes computing resources and can significantly slow the determination of an appropriate model.
There is therefore a need to take dynamic constraints into account as early as possible when determining the geological model, in order to optimize computing resources.